Greetings. Welcome to the Champions Oncology third quarter fiscal year 2025 earnings call. At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. Please note this conference is being recorded. I will now turn the conference over to your host, Ronnie Morris, Chief Executive Officer. You may begin. Good afternoon. I am Ronnie Morris, CEO of Champions Oncology. Joining me today is David Miller, our Chief Financial Officer. Thank you for joining us for our quarterly earnings call. Before I begin, I'll remind you that we'll be making forward-looking statements during today's call and that actual results could differ materially from what is described in those statements. Additional information on factors that could cause results to differ is available in our Forms 10-Q and Form 10-K. A reconciliation of non-GAAP financial measures that may be discussed during the call to GAAP financial measures is available in the earnings release. Q3 marked a transformative quarter for Champions Oncology, underscored by our record revenue of $17 million and the successful closure of our inaugural data deal. Our core services business remains at the forefront, driven by our industry-leading PDX Bank and its precisely characterized multiomic data, which has become the foundation for the pharmacology studies that have been used broadly by the biopharma industry. Throughout the year, we have dedicated ourselves to strengthening our teams and refining our processes, resulting in enhanced quality, increased efficiency, and scalability, which in turn have led to improved cost management and profitability. As we look ahead, we maintain a cautiously optimistic outlook for a rebound in our industry sector, with customers beginning to expand their R&D budgets and a slight recovery in the capital-raising environment for the biotech industry. Despite the mild improvement in the sector, the environment remains tight, leading to potential performance volatility. However, the overall trend suggests promising opportunities for long-term growth. A significant differentiator for Champions has always been our PDX Bank, offering pharmaceutical and biotech companies invaluable insights for drug development. By consistently expanding our collection of unique tumor models and enhancing their characterization, we have developed a robust multiomic data set with substantial potential for both drug discovery and development. This data set serves as a vital resource for our pharma partners, who gain access to model-specific data. With the rise of AI, which can extract deeper insights from the biological data, the demand for our data set has notably increased in both breadth and depth. Recognizing this shift, we are actively exploring ways to extract greater value from this data. The recently closed data deal exemplifies our strategic vision, where we licensed our existing deep multiomic data set while also acquiring prospective omic data sets from our unique bank of tumor models. This continued expansion of our data set aligns with our mission to create the world's most comprehensive biological data set from a clinically relevant tumor population. Such a data set aims to bridge the gaps in existing data used for AI and ML-mediated discovery workflows, ultimately transforming how the biopharmaceutical industry approaches target and biomarker discovery, as well as pipeline management. Over the past few years, we have worked diligently to enhance this data platform, pioneering the use of deep multiomic data sets in oncology discovery. The biopharmaceutical sector is now recognizing the immense untapped value within this type of data set, shifting away from classical data sets that offer broad insights but lack depth. We are well-positioned to take the lead in this evolving landscape, generating significant traction and enthusiasm for our initiative to build the world's deepest clinically relevant multiomic data set. However, I must caution that while we are excited about the initial validation of our strategy and continue to engage with other potential customers to build our opportunity pipeline, it remains premature to forecast the number of deals, their average size, or the frequency with which they will occur. Consequently, we are not yet in a position to project the data revenue contribution to our overall results or its impact on our bottom line. In the coming quarters, we hope to secure additional deals that will provide clarity on these important questions. Regarding Corellia, our wholly-owned drug development subsidiary, we are highly optimistic about the targets and compounds we have developed using our proprietary data. Our team is actively engaged in discussions to raise capital for the company while carefully weighing the impact on our bottom-line results. Despite the challenging funding environment, we have partnered with experienced bankers to bolster our capital-raising efforts, and both we and our advisors remain hopeful about the outlook. In summary, as highlighted during this call, Q3 was a groundbreaking quarter for us. We are excited about the potential of our core business, and although we face some challenges, we believe we are on a path towards long-term growth. The successful completion of our first data deal represents an initial validation of our strategic vision, signifying that our data asset is poised to evolve into a transformative data business for Champions Oncology. Now, I will hand the call over to David Miller for a more detailed review of our financial results. Thanks, Ronnie. Our full results on Form 10Q will be filed with the SEC by Monday, March 17th. As Ronnie highlighted, we had a record-breaking quarter with total revenues surpassing $17 million and adjusted EBITDA hitting a record high. Research service revenue was $12.5 million compared to $12 million in the year-ago period, and our data revenue contribution was $4.5 million, reinforcing the early traction of our new platform. On a GAAP basis, our income from operations for the third quarter was $4.5 million compared to our loss of $2.6 million in the prior year. This included $600,000 in non-cash expenses related to stock-based compensation and depreciation. Excluding these items, adjusted EBITDA was a record $5.2 million compared to an adjusted loss of $1.7 million in the prior year. Turning the focus to our cash-based results, total cost of sales was $6.6 million compared to $7.8 million in our third quarter of last year, a decrease of 16%. The decrease was primarily due to our reduction in salary expense, other lab costs, and outsourced lab services. Our gross margin for the quarter was 61%, lifted by the high-margin data revenue. Our research service margins also improved, increasing to 48% compared to 35% for the same period last year. Our research service margins will fluctuate over the next two quarters, with some expected volatility in revenue and cost of sales, but we anticipate long-term margin expansion exceeding 50% as long-term revenue grows. Our operating expenses reflected our commitment to disciplined cost management. Our R&D expense declined $500,000, or 21%, to $1.7 million, as we optimized spending while maintaining key investments in our core business. Our sales and marketing expenses remained stable at $1.8 million, and our G&A expense declined $200,000 to $1.8 million, primarily due to reductions in salary expense. Summarizing our year-to-date results for the first three quarters, total revenue was $45 million compared to $36 million for the first three quarters of 2024, an increase of 22%. Total cost of sales was $21 million compared to $21.9 million, a decrease of $900,000, or 4%. Total gross margin was 53% compared to 40% for the same period last year, with the improvement coming from the high-margin data revenue along with the operational efficiencies implemented, which enabled us to improve on our revenue conversion and maintain our costs. Research service margins were 48% compared to 40% for the three quarters ended January 21, 2024, and total operating expenses were down approximately $3.8 million compared to last year, primarily from reductions in R&D expense. The result was adjusted EBITDA of $8.3 million compared to adjusted loss of $4.8 million through nine months of fiscal 2024. Now, turning to cash, we ended the quarter with $3.2 million of cash on the balance sheet and no debt. For the quarter, cash generated by operating activities was $900,000, and cash used in investment activities was approximately $500,000. The net $400,000 quarterly increase in cash was primarily from an improvement in operational results offset by an increase in accounts receivable. Our balance sheet is solid, and our cash position is poised to increase in the coming quarters as our long-term operational results continue to improve and we collect on our new data revenue stream. To summarize, Q3 was a milestone quarter, with record-breaking financial performance and successful execution of our first data licensing agreement. While we anticipate short-term volatility in research service revenue, we remain confident in our long-term growth trajectory. We have reaffirmed our full-year revenue growth guidance of 10-15% and continue to focus on expanding our data business, enhancing profitability, and driving shareholder value. We look forward to updating you on our progress during our year-end earnings call in July. We'll now open the call to Q&A. Thank you. At this time, we will be conducting a question-and-answer session. If you would like to ask a question, please press star one on your telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star two to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. One moment, please, while we poll for questions. Once again, please press star one if you have a question or a comment. The first question comes from Matt Hewitt with Craig-Hallum. Please proceed. Hello. This is Toph Coron for Matt Hewitt. I do not know if I missed this. You guys kind of cut out there for a little bit. Regarding the licensing deal, could you please indicate how it is constructed? Are there any other opportunities in the pipeline? Thank you. Yeah. The licensing deal that we signed was for a portion of our data, and it was a one-time fee. In terms of the pipeline, we are actively talking to multiple partners and customers from the biotech and pharma industry about the power and the value of our data. That is something that we hope to continue to discuss over the next coming quarters. Okay. Thank you. Given the uncertainty we've seen the past few weeks regarding tariffs, budget cuts, do you see any impact on your conversations with customers about those? Yeah. I don't know if the tariffs themselves necessarily have impacted us, but certainly, it continues to be a tighter environment out there, and it's something we watch carefully. I think, to a certain extent, based on our superior reputation as well as that we work with many, many companies, I think it's shielded us a little bit from the environment, but it still remains a tight environment out there, especially in the biotech sector. I don't know if the tariffs have had any specific effect, and it could be too early to see those effects. Certainly, with regards to the biotech sector in general, I think it's still not as strong as we had seen it a couple of years ago and as strong as we would like it. Okay. So then I would take it with the weakness you're seeing in the biotech sector, is that directly translating to the implementation of these early studies and the demand from customers there, or is that not as direct as I'm thinking? I think it's certainly had an effect. I think we have done, as we've talked about many years, we've done a lot to weather that, both on trying to be more careful with our customer base and focusing more on some of the larger biopharmas over the last year and a half, as well as on the operational side, just making sure our processes are in place and we're much more efficient and scalable. I think we've attacked the tough environment both from a customer acquisition as well as an expense perspective. Having said that, it is still a challenging environment out there, but I think we've been handling it well. Have you seen anything that gives you hope coming up in maybe starting this year that there will be a turnaround in customer demand, specifically in biotech? I think that it's sector-specific. I think that there's certainly still a lot of investment in the pharma and biotech. There's still certainly a lot of investment in oncology. There are definitely pockets of certain types of targeted therapies that continue to be exciting. While I would say it's definitely still a mildly challenging time, I think there's still a lot of activity. I think it's certainly slightly better than it was, let's say, a year and a half ago. There are some silver linings. I just don't think that it's gotten back to the place where we saw it a couple of years ago and where we all wanted to get to. Okay. That's all for me. Thank you. You're welcome. Once again, if you have a question or a comment, please press star one on your touch-tone phone. The next question comes from Maj Soueidan with Geo Investing. Please proceed. Hello. Hey, thanks. That's Maj Soueidan, by the way, from Geo Investing. Relatively new to the story, although I followed the company for a long time, but never really got into it much. We started covering the company recently. This whole data thing really is very intriguing. I have two questions right now. The first question being around, forgive me too for my ignorance regarding that subsidiary you talked about, that you might have to raise some capital for that subsidiary. Can you give me some color in terms of are you raising money through the subsidiary, through the company's parent company? What does it mean for capital structure for the company? What are the common capital-raising mechanisms you're looking at to do that? As an investor, how should I think about that? I'll pause for that answer and then come back with our next question. Yeah. A couple of years ago, when we decided that our data and we had become profitable, and we decided that we really wanted to focus a little more on our data, we had a couple of different kind of vectors that we were looking at. One was just the raw data and the value of the data. One of the others was we had this data. We had a lot of deep biological data, a lot of response data, and we felt like that would be a great place to see if we could find some targets and start to develop some novel drugs against these novel targets. That's kind of what we set out to do. We're really excited about that effort. It's a separate company. It's a separate team. Legally, it's been separated from Champions. It's a true spinout, wholly owned because we right now have been the only one funding it. We got to the point now where Champions can't continue to fund it because we really wanted to get to phase one, phase two trials, and that requires a lot of capital. We are out there raising capital. Our expectation after we raise the capital is that Champions will retain a percentage of those businesses. It will be an asset. It will have a different investor base, which is a different type of investor base than Champions Oncology investor base. It's more of a drug discovery investor base. That's kind of how we're thinking about this, and that's what we're out there trying to raise money for. Excellent. You guys aren't going to have to raise an equity for this. You're looking for just capital now outside CSBR's capital structure to help kind of fund this. This isn't going to affect our ownership interest in CSBR's cash flow. Correct. It's not going to affect the cash flow, and it's only going to be an asset that, hopefully, if we raise money, attractive valuation is going to be additive to the value of a Champions Oncology shareholder. Excellent. Excellent. All right. On the data side, this new what you're doing now, I think, is very awesome. I think it's where a lot of the industry is going or an opportunity that I think others are kind of exploring. Jensen has talked about it a little bit. I think even the administration has talked about using AI to kind of help with cancer research. The question I have more here is, I mean, I know this is kind of a new model for you, and you're kind of maybe, I'm assuming, kind of exploring how you're going to price the model. This one's still, I guess, a licensing fee. Are you exploring other ways of maybe selling this data as you move through this and understand it more and what your customers want? I'd like to understand maybe, before I have my third question, what that might look like in the future. Yeah. We're exploring all aspects of, so if you think about, we have an asset that we believe is valuable. It's our data. And then there are customers, and customers come in different sizes and flavors. There's a couple of different ways you can license that data. You can license it out for a fee, for a license fee. You can license it out for a fee plus some type of royalty or milestones. There's all these different levers. We're certainly having discussions to certain smaller biotechs that are obviously much more interested in potentially giving royalties and milestones. For some of the larger pharma, they're more interested in just paying for a license fee. Everyone's a little bit different. We're looking at different models. Right now, for us, the most important thing is to understand the value and to speak to enough customers to really get them to understand the value of our data and to use some of our data and play with our data so they can understand why this is so valuable. That is the first step, and that is kind of the step we are in right now. Okay. Over time, you would anticipate, potentially, if this works out, that you'll have a mix of large licensing data, but also just maybe a recurring revenue component to some of the type of arrangements you might get into depending on the biotech company or pharma company. Yeah. It's certainly something we think about a lot, and we're looking at different models. We're not reinventing the wheel. These have been done before. We're trying to learn, and we're trying to understand what the market will bear. It's going to be a little bit different for different customers, but we're early on. Right now, we were excited about the first deal, which was proof of concept, and we have a couple others in the pipeline. As we continue to go, I anticipate, like the rest of our business, we will continue to evaluate other opportunities and other possibilities of how we structure deals. Okay. Regardless of what you did, this is definitely a very high-gross margin business that a lot of it flows right to the bottom of the line. Correct. Okay. Depending on licensing or recurring. All right. In your last conference call, you kind of mentioned, and you mentioned it today kind of a little bit, that a lot of this kind of data movement, this movement to go data licensing model, a lot of it came from actually customers were asking you, right? There was a lot of inbound kind of inquiries from your customers. I'm wondering how that is that where most of the interest is coming from with this new contract, for example, from an existing customer or a new customer? I guess there's two things. What opportunity do you see with your own customer base, right? Do you see this as an opportunity to expand your customer base? That's what I'm all waiting for. Yeah. I think it's both. You have to remember we work with between 400 and 500 of the pharma and biotech companies. We work with a large number of the biopharma companies within oncology. We're fairly well-known, and we work with a lot of them. Yes, we certainly have a large audience. We're out there talking to them about our data. Clearly, still, the bread and butter and the core business is the largest part of our business where people send us their compounds, and we do studies for them, and we give them a lot of valuable insights on their drugs. The plan is to both for our customer base and for our non-customer base to be going out there and talking to people about the value of our data and why we think it's important. Okay. When a customer maybe, let's say, like you did this time, has to buy a licensing arrangement with one big pump of data, I'm assuming, do you see the opportunity? Is this one and done with a customer? Is there a reason for them to keep coming back? I'd like to understand that a little bit. I know there's an option for them to come back with $3 million here, but maybe talk about that. Yeah. We see data, and this is, I think, a little bit of the difference between us and a lot of other groups. We've always seen data as something that continues to grow. We have a hundred, I'll give you an example. We have 100 lung cancer patients, and our first layer of data many years ago was a genomic profile. Then we went to a transcriptome profile, and then we added a layer of proteomics and phosphoproteomics, and then we added other layers. We continue to add layers so that the deeper understanding of the interactions of all the pathways within that tumor and also the interaction with different responses that that tumor has had both in the clinic and in the PDX model. We keep enriching the data, and that's the beauty of kind of our bank and our data. As there are more opportunities to get more refined with the characterization, we keep characterizing these tumors and understanding the biology deeper and deeper. Now, with the advent of AI, before it was much, much more complicated because we created a ton of data. Now, with the advent of AI, these data sets just become more and more important, and there is a lot that can be generated and learned from it. Yes, our plan is to continue to generate more data from these data sets, and that seems to be resonating well with our customers. Great. Great. Just can you give me an idea, I guess, an idea in terms of the competition you're seeing out there? I think you said you wanted to be a leader in this. Are you seeing a lot more companies that you compete against do the same thing right now, or do you think you are one of the first ones really to kind of embark on this whole thing? Yeah. I think a lot of companies have been selling data for a long time. I think for a long period of time, most of the companies have been selling very, what I would call, longitudinal data with hundreds of thousands of patients with a small amount of data on each patient. We're one of the first who are doing it a little bit differently, where not as many patients, but with each patient and each tumor, we're going very deep and really understanding the interactions at a very deep molecular and a biological level. From a discovery standpoint, from understanding the effect of a drug on the biology of a tumor and looking for new targets, I think we have a very unique approach, and I think it's the right time for it because the capabilities with AI and machine learning really avail this type of a data set to be able to unearth some of the deeper insights. That's kind of a little bit of a different approach that I think is the right time for this right now, and that's our goal. Okay. My last question, going back to your legacy business, are you seeing AI helping you in your own kind of legacy business, doing your research for companies? Not so much yet. We haven't really seen that effect yet. It doesn't mean it's not going to come. It's just right now, we haven't really seen the impact of that on kind of the core business. Okay. Hey, thanks, man. You're welcome. The next question is from Edward Gilmore, private investor. Edward, please proceed. Thank you. Hi, Ronnie. Thanks for taking my call. I just had a couple of quick questions. Of course. On the AI side of things with the data, do you see potential for the data to be used outside of drug discovery and research, for example, maybe more in a clinical setting with identification and evaluation of tumors? You mean in terms of a biomarker approach? Yes. Yeah. I've always felt, I mean, we've always felt that there's two real best uses for our data, for the deep data of understanding these tumors. One was from a discovery perspective, and the other was from kind of a biomarker perspective. The discovery perspective is kind of a better path right now. The biomarker path is still a super interesting path. It's just that, for whatever reason, most of the biopharma over the last 10 years have not been that interested in finding the right biomarker for their drug. A lot of reasons for that. I know they talk about biomarkers a lot, but we really haven't seen that much interest in really understanding what is that super patient population that they should only go for in a trial. I think it's important to them to kind of figure out the trial to make sure the trial is successful, but I don't know that they're super keen on finding that very specific biomarker that's going to restrict or just kind of narrowly pick out the patients in the clinic that are only going to work for that drug. It certainly could be a super good, it's certainly a super smart way to use our data to also look for clinical biomarkers. As of yet, that I don't think has been the driving force for people to use our data as much. Okay. Thanks. Stay tuned for that. The second question, a couple of weeks ago, you guys put out a press release about the upcoming Association for Cancer Research meeting and announced that you had a number of abstracts that were accepted for presentation there. I wonder if you could just, from your perspective, to investors, kind of give a little bit more color on that and how excited you are and what you kind of expect to come from that because I know AI is going to be a heavy topic that's mentioned and talked about there. Yeah. We have always been an organization that's kind of not so much like a CRO but more of a scientific leader, and that's the way our partners see us. I think it was important for us to show that we continue to be on the cutting edge, doing a lot of R&D, and just continuing to be innovative and thinking about how do we develop the assays to just help the pharma partners that we work with just to develop the best drugs and get the best preclinical package that's going to give them the best chance in the clinic. We are excited about the continued number of posters because it shows that we continue to innovate. We continue to think of ourselves as an R&D organization to a certain extent, and we're excited about it. Certainly, those abstracts will become available, and you'll be able to read them. Okay. Thank you. Sorry, one more quick question. On the PDX data side, do you have a team set up now internally that's leading that as far as how you do customer acquisition, or what's kind of the go-to-market strategy there? I'll drop off. In terms of what? In terms of what? I'm not sure I understand the question. In terms of how you're communicating to prospective customers about how they can find out that they have access to be able to license the data if they're a pharma or biotech company, just how they're discovering that they can find out. In terms of the data side? Yes. In terms of the data side? Yeah. We have a separate team that handles the data side. We also have a team that handles just the core business, but there's a lot of crossover because it's a lot of the same customers. So there's a lot of crossover between the regular sales team and the business development team as well as the team that's handling the data strategy. Okay. Thank you. You're welcome. The next question is from George Marema with Pareto Ventures. Please proceed. Yeah. Hi. Thanks for taking my call. I had a question on this $5 million license deal. Kind of roughly speaking, of all your data, the entire pie, how big a slice of the pie represented this deal? Is it 100%, 5%? How much data did they buy for $5 million out of the total data? Yeah. That isn't something that we have publicly announced. We don't really talk about kind of how much people pay for different data. Different people have different deals depending on early, late. That isn't something that we have spoken about publicly. Okay. On your kind of go-to-market on this internally, do you have dedicated salespeople for this, or how exactly are you marketing and selling these data licenses currently? Yeah. We have a dedicated team. We have a general manager, Matt Newman. We brought in the head of our data sciences. We have a couple of business development people who have a lot of experience in this area. Yeah, we have a team now assembled. It's a fairly new team over the last six months to a year, but we have a dedicated team that's out there talking about our data. Did I hear earlier in the call that you do have a couple few that are in the pipeline in 2025 here so far? I'm sorry. Can you repeat that? You cut out for a second. Yeah. Yeah. Did I hear it right that you have two or three deals that are in the pipeline currently on data licensing deals? I believe what you heard was we have a pipeline, and we continue to talk to people, and we did not mention the number of deals that are in the pipeline. I think that. Thank you. I'll just add that some of the deals will be large. Some of the deals will be medium. Some of the deals will be small. I think the goal is to get people to utilize our data and continue to make them a believer and use more and more data over time. Okay. All right. Thank you, Ronnie. You're welcome. If there are any remaining questions, please indicate so by pressing star one. We have no further questions in the queue. I'd like to turn the floor back to management for closing remarks. Thank you very much. As we mentioned, this is an exciting quarter for Champions Oncology. We look forward to having our fiscal year-end call mid-July. Until then, stay tuned, and we're excited about the progress that we're making, and we look forward to following up with everybody. Thank you for joining. This concludes today's conference, and you may disconnect your lines at this time. Thank you for your participation.